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<TITLE>Project on Mathematics and Computation</TITLE>

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<td> <!WA3><A HREF="http://www.swiss.ai.mit.edu/~hal/hal.html"><address><b>Harold Abelson</b></a>,<br>Class of 1922 Professor of Computer Science and Engineering</address>
	<!WA4><A HREF="http://www.swiss.ai.mit.edu/~gjs/gjs.html"> <address><b>Gerald Sussman</b></a>,<br>Matsushita Professor of Electrical Engineering</address></td>
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Solving scientific problems increasingly depends on
high-speed computation, careful planning of numerically
based experiments, and high-level, qualitative
interpretation of large volumes of quantitative data.
Working jointly with the Artificial Intelligence (AI)
laboratory, researchers within MIT's Project on Mathematics
and Computation are developing a wide range of intelligent
computation tools to help scientists and engineers
understand mathematical models of physical processes. Some
of the Project's goals include efficient new algorithms,
specialized hardware, and "smart" programs that comprehend
measured or numerical data.   Much of our work in
scientific computation is based on AI methods. We have used
computer-vision techniques, for example, to create programs
that "look at" and qualitatively interpret graphical
results of numerical experiments. Other programs can
construct numerical simulation systems of dynamically
complex processes (such as oscillating chemical reactions
and nonlinear vibrating beams), then automatically
incorporate them into qualitative-analysis programs. Such
programs can also generate high-level summary descriptions
-- graphically and in English -- of numerical experiments,
similar to the descriptions that appear in published
scientific and engineering papers.
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To support the automatic construction of numerical
procedures, we are seeking ways to express numerical
algorithms in terms of high-order procedural abstractions.
Sophisticated numerical routines thus can be assembled by
mixing and matching components from a numerical library.
The large library of routines we are now assembling will
contain symbolic methods as well as numeric ones.
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Our work rests on the <!WA5><A HREF="http://www.swiss.ai.mit.edu/schene-home.html">Scheme dialect of Lisp</a> and the Scheme
programming environment, which we invented and continue to
develop. We have joined with other Scheme users and
developers to formally standardize this dialect through the
IEEE. We expect that our freely available native-code
<!WA6><a href=ftp://ftp-swiss.ai.mit.edu/pub/scheme-7.3/>Scheme compiler</a> will offer performance comparable to that
of the best commercial Lisp compilers.


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